Data Mining pp 663-693 | Cite as

Privacy-Preserving Data Mining

Chapter

Abstract

A significant amount of application data is of a personal nature. These kind of data sets may contain sensitive information about an individual, such as his or her financial status, political beliefs, sexual orientation, and medical history. The knowledge about such personal information can compromise the privacy of individuals. Therefore, it is crucial to design data collection, dissemination, and mining techniques, so that individuals are assured of their privacy.

Keywords

Sensitive Attribute Data Mining Algorithm Bibliographic Note Anonymization Algorithm Oblivious Transfer Protocol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.IBM T.J. Watson Research CenterYorktown HeightsUSA

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